code: def exp_lgb_0():
      return CVExperiment(
          model_initializer=LGBMClassifier,
          model_init_params=dict(
              boosting_type="gbdt",
              num_leaves=5,
              n_estimators=10,
              max_depth=5,
              min_child_samples=1,
              subsample=0.5,
              verbose=-1,
          ),
      )
  
file_path: hyperparameter_hunter/tests/smoke_tests/test_lightgbm.py
imports: from hyperparameter_hunter import Environment, CVExperiment, Real, Integer, Categorical
  from hyperparameter_hunter import BayesianOptPro
  from hyperparameter_hunter.i_o.result_reader import has_experiment_result_file
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data
  import pytest
  from lightgbm import LGBMClassifier
  from sklearn.metrics import f1_score
label_desc: Use image node_id 2 for calling a global function with example usage: exp_lgb_0() and returns: CVExperiment